Power in unity: Forming teams in large-scale community systems

Aris Anagnostopoulos, Luca Becchetti, Carlos Castillo, Aristides Gionis, Stefano Leonardi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

77 Citations (Scopus)

Abstract

The internet has enabled the collaboration of groups at a scale that was unseen before. A key problem for large collaboration groups is to be able to allocate tasks effectively. An effective task assignment method should consider both how fit teams are for each job as well as how fair the assignment is to team members, in terms that no one should be overloaded or unfairly singled out. The assignment has to be done automatically or semi-automatically given that it is difficult and time-consuming to keep track of the skills and the workload of each person. Obviously the method to do this assignment must also be computationally efficient. In this paper we present a general framework for task-assignment problems. We provide a formal treatment on how to represent teams and tasks. We propose alternative functions for measuring the fitness of a team performing a task and we discuss desirable properties of those functions. Then we focus on one class of task-assignment problems, we characterize the complexity of the problem, and we provide algorithms with provable approximation guarantees, as well as lower bounds. We also present experimental results that show that our methods are useful in practice in several application scenarios.

Original languageEnglish
Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
Pages599-608
Number of pages10
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 - Toronto, ON, Canada
Duration: 26 Oct 201030 Oct 2010

Other

Other19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
CountryCanada
CityToronto, ON
Period26/10/1030/10/10

Fingerprint

Task assignment
Assignment
Assignment problem
Guarantee
Lower bounds
Fitness
Workload
Scenarios
Approximation
World Wide Web

Keywords

  • Scheduling
  • Task assignment
  • Team formation

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

Cite this

Anagnostopoulos, A., Becchetti, L., Castillo, C., Gionis, A., & Leonardi, S. (2010). Power in unity: Forming teams in large-scale community systems. In International Conference on Information and Knowledge Management, Proceedings (pp. 599-608) https://doi.org/10.1145/1871437.1871515

Power in unity : Forming teams in large-scale community systems. / Anagnostopoulos, Aris; Becchetti, Luca; Castillo, Carlos; Gionis, Aristides; Leonardi, Stefano.

International Conference on Information and Knowledge Management, Proceedings. 2010. p. 599-608.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Anagnostopoulos, A, Becchetti, L, Castillo, C, Gionis, A & Leonardi, S 2010, Power in unity: Forming teams in large-scale community systems. in International Conference on Information and Knowledge Management, Proceedings. pp. 599-608, 19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10, Toronto, ON, Canada, 26/10/10. https://doi.org/10.1145/1871437.1871515
Anagnostopoulos A, Becchetti L, Castillo C, Gionis A, Leonardi S. Power in unity: Forming teams in large-scale community systems. In International Conference on Information and Knowledge Management, Proceedings. 2010. p. 599-608 https://doi.org/10.1145/1871437.1871515
Anagnostopoulos, Aris ; Becchetti, Luca ; Castillo, Carlos ; Gionis, Aristides ; Leonardi, Stefano. / Power in unity : Forming teams in large-scale community systems. International Conference on Information and Knowledge Management, Proceedings. 2010. pp. 599-608
@inproceedings{e3e642b31da54421a166d50b23c50574,
title = "Power in unity: Forming teams in large-scale community systems",
abstract = "The internet has enabled the collaboration of groups at a scale that was unseen before. A key problem for large collaboration groups is to be able to allocate tasks effectively. An effective task assignment method should consider both how fit teams are for each job as well as how fair the assignment is to team members, in terms that no one should be overloaded or unfairly singled out. The assignment has to be done automatically or semi-automatically given that it is difficult and time-consuming to keep track of the skills and the workload of each person. Obviously the method to do this assignment must also be computationally efficient. In this paper we present a general framework for task-assignment problems. We provide a formal treatment on how to represent teams and tasks. We propose alternative functions for measuring the fitness of a team performing a task and we discuss desirable properties of those functions. Then we focus on one class of task-assignment problems, we characterize the complexity of the problem, and we provide algorithms with provable approximation guarantees, as well as lower bounds. We also present experimental results that show that our methods are useful in practice in several application scenarios.",
keywords = "Scheduling, Task assignment, Team formation",
author = "Aris Anagnostopoulos and Luca Becchetti and Carlos Castillo and Aristides Gionis and Stefano Leonardi",
year = "2010",
month = "12",
day = "1",
doi = "10.1145/1871437.1871515",
language = "English",
isbn = "9781450300995",
pages = "599--608",
booktitle = "International Conference on Information and Knowledge Management, Proceedings",

}

TY - GEN

T1 - Power in unity

T2 - Forming teams in large-scale community systems

AU - Anagnostopoulos, Aris

AU - Becchetti, Luca

AU - Castillo, Carlos

AU - Gionis, Aristides

AU - Leonardi, Stefano

PY - 2010/12/1

Y1 - 2010/12/1

N2 - The internet has enabled the collaboration of groups at a scale that was unseen before. A key problem for large collaboration groups is to be able to allocate tasks effectively. An effective task assignment method should consider both how fit teams are for each job as well as how fair the assignment is to team members, in terms that no one should be overloaded or unfairly singled out. The assignment has to be done automatically or semi-automatically given that it is difficult and time-consuming to keep track of the skills and the workload of each person. Obviously the method to do this assignment must also be computationally efficient. In this paper we present a general framework for task-assignment problems. We provide a formal treatment on how to represent teams and tasks. We propose alternative functions for measuring the fitness of a team performing a task and we discuss desirable properties of those functions. Then we focus on one class of task-assignment problems, we characterize the complexity of the problem, and we provide algorithms with provable approximation guarantees, as well as lower bounds. We also present experimental results that show that our methods are useful in practice in several application scenarios.

AB - The internet has enabled the collaboration of groups at a scale that was unseen before. A key problem for large collaboration groups is to be able to allocate tasks effectively. An effective task assignment method should consider both how fit teams are for each job as well as how fair the assignment is to team members, in terms that no one should be overloaded or unfairly singled out. The assignment has to be done automatically or semi-automatically given that it is difficult and time-consuming to keep track of the skills and the workload of each person. Obviously the method to do this assignment must also be computationally efficient. In this paper we present a general framework for task-assignment problems. We provide a formal treatment on how to represent teams and tasks. We propose alternative functions for measuring the fitness of a team performing a task and we discuss desirable properties of those functions. Then we focus on one class of task-assignment problems, we characterize the complexity of the problem, and we provide algorithms with provable approximation guarantees, as well as lower bounds. We also present experimental results that show that our methods are useful in practice in several application scenarios.

KW - Scheduling

KW - Task assignment

KW - Team formation

UR - http://www.scopus.com/inward/record.url?scp=78651277509&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78651277509&partnerID=8YFLogxK

U2 - 10.1145/1871437.1871515

DO - 10.1145/1871437.1871515

M3 - Conference contribution

AN - SCOPUS:78651277509

SN - 9781450300995

SP - 599

EP - 608

BT - International Conference on Information and Knowledge Management, Proceedings

ER -